Level: Beginner
The structural equation models (SEM) platform continues to evolve into a more complete and platform. Two key features in JMP Pro 17 are (1) a link between Factor Analysis and SEM to facilitate survey development, and (2) multiple-group analysis. We demonstrate these features with data inspired by Yamamura and Takehira (2017), where Japanese students were surveyed on their learning motivation. Attendees will learn to build powerful surveys and use them to gain insights about subpopulations
The Structural Equation Modeling (SEM) platform continues to evolve into a more complete and powerful platform. The main new features in JMP Pro 17 are (1) the linking of exploratory factor analysis with SEM (which is useful for designing questionnaire questions) and (2) multi-population analysis. These two features will be introduced using a study by Yamamura and Takehira (2017), which examined the academic motivation of university students at a Japanese university. In this presentation, we will show how to design a survey and obtain information about subpopulations from the survey.
[Presenter Profile]
Laura Castro-Schilo works on structural equations models in JMP. She is interested in multivariate analysis and its application to different kinds of data; continuous, discrete, ordinal, nominal and even text. Previously, she was Assistant Professor at the LL Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. Castro-Schilo has a PhD in quantitative psychology from the University of California, Davis.
Laura Castro-Schilo works with structural equation modeling in JMP. She is interested in multivariate analysis and its applications to a variety of data types, including continuous, discrete, ordinal, nominal, and text. She previously served as an assistant professor in the L.L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. She received her Ph.D. in quantitative psychology from the University of California, Davis.
